The structure of microbial association networks was investigated for seventeen studies on food bacterial communities using the CoNet app. The results were compared with those for host and environmental microbiomes. Microbial association networks of food bacterial communities shared several properties with those of host microbiomes, although they were less complex and lacked a scale-free, small world structure that is characteristic of environmental microbial communities. This may depend on both the initial contami- nation pattern, whose main source is the raw material microbiome, and on the copiotrophic nature of food environments, with lack of well defined, specific niches. The selective factors which are charac- teristic of fermentation and spoilage drastically simplified microbial association networks and showed the emergence of negative hubs. Co-presence and mutual exclusion networks had a radically different structure, with high clustering coefficient in the first and high heterogeneity in the latter. Node prop- erties (degree, positive degree, betweenness centrality, abundance) can be combined in plots, which allow a rapid identification of hub species. The combined use of three network inference tools (CoNet, SparCC, and SPIEC-EASI) confirmed that microbial association network detection is method specific, but several coherent copresence or mutual exclusion relationships were detected by at least two different methods.
Structure of association networks in food bacterial communities
Parente, Eugenio
Writing – Original Draft Preparation
;Zotta, TeresaWriting – Review & Editing
;
2018-01-01
Abstract
The structure of microbial association networks was investigated for seventeen studies on food bacterial communities using the CoNet app. The results were compared with those for host and environmental microbiomes. Microbial association networks of food bacterial communities shared several properties with those of host microbiomes, although they were less complex and lacked a scale-free, small world structure that is characteristic of environmental microbial communities. This may depend on both the initial contami- nation pattern, whose main source is the raw material microbiome, and on the copiotrophic nature of food environments, with lack of well defined, specific niches. The selective factors which are charac- teristic of fermentation and spoilage drastically simplified microbial association networks and showed the emergence of negative hubs. Co-presence and mutual exclusion networks had a radically different structure, with high clustering coefficient in the first and high heterogeneity in the latter. Node prop- erties (degree, positive degree, betweenness centrality, abundance) can be combined in plots, which allow a rapid identification of hub species. The combined use of three network inference tools (CoNet, SparCC, and SPIEC-EASI) confirmed that microbial association network detection is method specific, but several coherent copresence or mutual exclusion relationships were detected by at least two different methods.File | Dimensione | Formato | |
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